Instructions to use mlx-community/GLM-OCR-5bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlx-community/GLM-OCR-5bit with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="mlx-community/GLM-OCR-5bit")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("mlx-community/GLM-OCR-5bit") model = AutoModelForMultimodalLM.from_pretrained("mlx-community/GLM-OCR-5bit", device_map="auto") - MLX
How to use mlx-community/GLM-OCR-5bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir GLM-OCR-5bit mlx-community/GLM-OCR-5bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 367 Bytes
a94611b | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"size": {"shortest_edge": 12544, "longest_edge": 9633792},
"do_rescale": true,
"patch_size": 14,
"temporal_patch_size": 2,
"merge_size": 2,
"image_mean": [0.48145466, 0.4578275, 0.40821073],
"image_std": [0.26862954, 0.26130258, 0.27577711],
"image_processor_type": "Glm46VImageProcessor",
"processor_class": "Glm46VProcessor"
}
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